Allele Mining of Exotic Maize Germplasm to Enhance Macular Carotenoids
Bibliographic record
Abstract
ABSTRACT Lutein and zeaxanthin are commonly referred to as the macular carotenoids, as they are localized to ocular tissues and their loss is associated with age‐related macular degeneration. Thirty‐four high‐carotenoid (HiC) lines exhibiting uniquely high concentrations of carotenoids resulted from allele mining of the Orange Flint race using traditional breeding techniques and visual selection for deep orange endosperm color. Total carotenoid concentrations of the HiC lines ranged from 50 to 101 μg g −1 dry weight (DW) with lutein and zeaxanthin concentrations as high as 66 and 65 μg g −1 DW, respectively, levels higher than reported in previous germplasm surveys. The HiC lines fall into three classes based on the accumulation of the major carotenoid: “high‐lutein,” “high‐zeaxanthin,” and “balanced.” Significant year effects were observed for carotenoid concentrations but not for profiles. During kernel development the pattern of carotenoid accumulation in the HiC lines did not appear to be different than in yellow corn belt dent lines. Collectively, the HiC lines represented only one y1 haplotype, 10 unique haplotypes of lcyE , and two unique haplotypes at crtRB1 Interestingly, previously identified diagnostic polymorphisms within lcyE did not appear to be useful in distinguishing between high‐lutein and high‐zeaxanthin HiC lines, and high β‐carotene levels were achieved despite the presence of a suboptimal crtRB1 allele. The HiC lines illustrate the utility of mining allelic variation from exotic sources coupled with the power of simple visual selection and the potential limitations of diagnostic polymorphisms.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".